Active oil debris monitor particle detection and monitoring system

ABSTRACT

A method for determining the presence of a particle while actively calculating and monitoring oil debris monitor phase angle in an oil system including collecting I and Q channel data from an oil debris monitor sensor; determining whether the I and Q data is symmetric; processing the I and Q channel data to identify a ferrous and nonferrous signal in response to the I and Q data being symmetric; processing the ferrous and nonferrous signals to determine if a particle is present; determining a symmetry factor from the I and Q channel data in response to the particle being present and confirming that the particle is present from the symmetry factor.

BACKGROUND

The present disclosure relates to an oil system for a gas turbine engineand, more particularly, to an on-board system to confirm whether or nota particle detection is valid.

Many types of mechanical machinery include various components thatrequire lubrication. For example, gas turbine engines typically havegears and bearings that require a lubricating liquid, such as oil, tolubricate and cool those gears and bearings during operation. Duringoperation, debris accumulates in the lubricating liquid. Because ofthis, lubrication systems typically include an oil debris monitor systemto sense metal debris in the oil. An oil debris monitor system isnormally used to flag the initiation or progression of mechanicalfailures in the lubricated mechanical machinery.

It is extremely difficult to validate the accuracy of an oil debrismonitor system while it is installed in a lubrication system. Thus, itis important to validate the accuracy of an oil debris monitor prior toit being installed in the lubrication system. It can also be difficultto reliably validate accuracy of an oil debris monitor in a lab withknown validation methods, especially in a lab that does not allow oil tobe present. An oil debris monitor phase angle is often used to classifydetected particle types (ferrous/nonferrous) through a mathematicaltransformation. Currently, the phase angle is hardcoded into the system.The phase angle is determined by an offline calibration test process andthe resultant value calculated. In legacy systems, the phase angleapplied to oil debris monitor data for particle detection is a fixedvalue in the software. However, the proper phase angle for an individualoil debris monitor is a function of system capacitance and inductance,so every oil debris monitor sensor phase angle is different and canchange based on system condition and related system components. The useof an improper phase angle can reduce the system capability to detectparticles and can also lead to particle type and size misclassification.Furthermore, a system phase angle should be fixed, and any suddenchanges or instability in phase angle may be indicative of systemdeterioration.

Analysis of ODM system raw data requires human expertise to confirmwhether or not a particle detection is valid. It is possible that in anoisy system, the background noise signature can generate a particlecount, even if the shape, by visual inspection, is not particle like.

SUMMARY

A method for determining the presence of a particle while activelycalculating and monitoring oil debris monitor phase angle in an oilsystem according to one disclosed non-limiting embodiment of the presentdisclosure includes: a) collecting I and Q channel data from an oildebris monitor sensor; b) determining whether the I and Q data issymmetric; c) processing the I and Q channel data to identify a ferrousand nonferrous signal in response to the I and Q data being symmetric instep b); d) processing the ferrous and nonferrous signals to determineif a particle is present; e) determining a symmetry factor from the Iand Q channel data in response to the possibility that the particle ispresent in step d); and f) confirming that the particle is present fromthe symmetry factor.

A further embodiment of any of the foregoing embodiments of the presentdisclosure includes that step b) comprises determining if the lobe peaksare symmetric.

A further embodiment of any of the foregoing embodiments of the presentdisclosure includes that the ferrous and nonferrous signals are used fordetection.

A further embodiment of any of the foregoing embodiments of the presentdisclosure includes that said step d) comprises filtering and phaseadjusting the ferrous and nonferrous signals.

A further embodiment of any of the foregoing embodiments of the presentdisclosure includes continually filling a buffer of the controller withthe I and Q channel data.

A further embodiment of any of the foregoing embodiments of the presentdisclosure includes converting the I and Q channel data to digital I andQ data within the controller on-board an aircraft.

A further embodiment of any of the foregoing embodiments of the presentdisclosure includes locating the oil debris monitor sensor within an oilsupply path.

A further embodiment of any of the foregoing embodiments of the presentdisclosure includes locating the oil debris monitor sensor within an oilreturn path.

A further embodiment of any of the foregoing embodiments of the presentdisclosure includes that the symmetry factor=peak/absolute value(valley) of the I and Q channel data.

A further embodiment of any of the foregoing embodiments of the presentdisclosure includes that the particle is rejected in response to thesymmetry factor being less than a threshold.

A further embodiment of any of the foregoing embodiments of the presentdisclosure includes that the example threshold is 1-4.

A further embodiment of any of the foregoing embodiments of the presentdisclosure includes that the symmetry factor is applied to the I channeldata.

A further embodiment of any of the foregoing embodiments of the presentdisclosure includes that the symmetry factor is applied to the Q channeldata.

An oil system for a gas turbine engine according to one disclosednon-limiting embodiment of the present disclosure includes: an oil flowpath; an in-line oil debris monitor sensor; and a control system incommunication with the in-line oil debris monitor sensor to determinewhether a particle is present from a symmetry factor of the I and Qchannel data.

A further embodiment of any of the foregoing embodiments of the presentdisclosure includes that the oil flow path is in communication with ageared architecture of the gas turbine engine.

A further embodiment of any of the foregoing embodiments of the presentdisclosure includes that the oil flow path is an oil supply path.

A further embodiment of any of the foregoing embodiments of the presentdisclosure includes that the oil flow path is an oil return path.

A further embodiment of any of the foregoing embodiments of the presentdisclosure includes a chip collector within the oil flow path.

A further embodiment of any of the foregoing embodiments of the presentdisclosure includes that the control system comprises a controlleron-board an aircraft.

The foregoing features and elements may be combined in variouscombinations without exclusivity, unless expressly indicated otherwise.These features and elements as well as the operation thereof will becomemore apparent in light of the following description and the accompanyingdrawings. It should be appreciated; however, the following descriptionand drawings are intended to be exemplary in nature and non-limiting.

BRIEF DESCRIPTION OF THE DRAWINGS

Various features will become apparent to those skilled in the art fromthe following detailed description of the disclosed non-limitingembodiments. The drawings that accompany the detailed description can bebriefly described as follows:

FIG. 1 is a schematic cross-section of an example gas turbine enginearchitecture.

FIG. 2 is a schematic cross-section of a geared architecture for a gasturbine engine.

FIG. 3 is a schematic diagram of an oil system for a geared architecturegas turbine engine.

FIG. 4 is a schematic diagram of a debris management system according toone disclosed non-limiting embodiment.

FIG. 5 is a block diagram representative of logic for the debrismonitoring system.

FIG. 6 is a schematic representation of a coordinate system to determinephase angle.

FIG. 7 is a graphical representation of a phase adjustment of the phaseangle for a ferrous and nonferrous particle by the controller.

FIG. 8 is a block diagram representative of a method that calculate thephase as shown in FIG. 5.

FIG. 9 is a graphical representation of a phase angle determination.

FIG. 10 is a graphical representation of a dynamically adjusted phaseangle determination.

FIG. 11 is a graphical representation of a software fixed phase angledetermination.

FIG. 12 is a graphical representation of raw ODM channel data.

FIG. 13 is a graphical representation of a dynamically adjusted phaseangle determination buffer in a stable condition as determined withinthe controller.

FIG. 14 is a block diagram representative of particle detection logicfor the logic for the debris management system shown in FIG. 5.

FIG. 15 is a graphical representation of the FFT of the controllerbuffer which contains only noise.

FIG. 16 is a graphical representation of the FFT of the controllerbuffer which contains a particle—note bow from 0 to 400 Hz peaked at 200Hz.

FIG. 17 is a graphical representation of the FFT of the particle alonescaled to 8192 pt. buffer.

FIG. 18 is a graphical representation of the FFT of the 8192-pt. buffercontaining particle overlaid with particle FFT.

FIG. 19 is a graphical representation of the FFT containing a particlewith the particle component removed compared to noise only FFT—note theFFT peaks are the same between buffer blocks after particle removal.

FIG. 20 is a graphical representation of the FFT of the particle alonevs. the FFT of particle containing buffer with the noise componentremoved.

FIG. 21 is a block diagram representative of particle detection logicfor the logic for the debris management system shown in FIG. 5.

FIG. 22 is a block diagram representative of particle detection logicaccording to another embodiment for the logic for the debris managementsystem shown in FIG. 5.

FIG. 23 is a graphical representation of the I and Q channel dataaccording to one embodiment.

FIG. 24 is a graphical representation of the I and Q channel dataconverted into ferrous and nonferrous signal data.

FIG. 25 is a table representative of the symmetry check to provides anadditional validity check for candidate particles.

FIG. 26 is a graphical representation of the I and Q channel dataaccording to another embodiment.

FIG. 27 is a graphical representation of the I and Q channel dataconverted into ferrous and nonferrous signal data.

FIG. 28 is a table representative of the symmetry check to provides anadditional validity check for candidate particles.

FIG. 29 is a graphical representation of the I and Q channel dataaccording to another embodiment.

FIG. 30 is a graphical representation of the I and Q channel dataconverted into ferrous and nonferrous signal data.

FIG. 31 is a table representative of the symmetry check to provides anadditional validity check for candidate particles.

DETAILED DESCRIPTION

FIG. 1 schematically illustrates a gas turbine engine 20. The gasturbine engine 20 is disclosed herein as a two-spool turbofan thatgenerally incorporates a fan section 22, a compressor section 24, acombustor section 26, and a turbine section 28. The fan section 22drives air along a bypass flowpath while the compressor section 24drives air along a core flowpath for compression and communication intothe combustor section 26, then expansion through the turbine section 28.Although depicted as a turbofan in the disclosed non-limitingembodiment, it should be appreciated that the concepts described hereinmay be applied to other engine architectures such as turbojets,turboshafts, and three-spool (plus fan) turbofans.

The engine 20 generally includes a low spool 30 and a high spool 32mounted for rotation about an engine central longitudinal axis Xrelative to an engine static structure 36 via several bearings 38. Thelow spool 30 generally includes an inner shaft 40 that interconnects afan 42, a low pressure compressor (“LPC”) 44 and a low pressure turbine(“LPT”) 46. The inner shaft 40 drives the fan 42 directly or through ageared architecture 48 that drives the fan 42 at a lower speed than thelow spool 30. An exemplary reduction transmission is an epicyclictransmission, such as a planetary or star gear system.

The high spool 32 includes an outer shaft 50 that interconnects a highpressure compressor (“HPC”) 52 and high pressure turbine (“HPT”) 54. Acombustor 56 is arranged between the high pressure compressor 52 and thehigh pressure turbine 54. The inner shaft 40 and the outer shaft 50 areconcentric and rotate about the engine central longitudinal axis X whichis collinear with their longitudinal axes.

Core airflow is compressed by the LPC 44, then the HPC 52, mixed withthe fuel and burned in the combustor 56, then expanded over the HPT 54and the LPT 46 which rotationally drive the respective high spool 32 andthe low spool 30 in response to the expansion. The shafts 40, 50 aresupported at a plurality of points by bearings 38 within the staticstructure 36.

With reference to FIG. 2, the geared architecture 48 includes a sun gear60 driven by a sun gear input shaft 62 from the low spool 30, a ringgear 64 connected to a ring gear output shaft 66 to drive the fan 42 anda set of intermediate gears 68 in meshing engagement with the sun gear60 and ring gear 64. Each intermediate gear 68 is mounted about ajournal pin 70 which are each respectively supported by a carrier 74.The input shaft 62 and the output shaft 66 counter-rotate as the sungear 60 and the ring gear 64 are rotatable about the engine centrallongitudinal axis A. The carrier 74 is grounded and non-rotatable eventhough the individual intermediate gears 68 are each rotatable abouttheir respective axes 80. An oil recovery gutter 76 is located aroundthe ring gear 64. The oil recovery gutter 76 may be radially arrangedwith respect to the engine central longitudinal axis A.

A replenishable film of oil, not shown, is supplied to an annular space72 between each intermediate gear 68 and the respective journal pin 70.One example applicable oil meets U.S. Military SpecificationMIL-PRF-23699, for example, Mobil Jet Oil II manufactured by ExxonMobilAviation, United States. Oil is supplied through the carrier 74 and intoeach journal pin 70 to lubricate and cool the gears 60, 64, 68 of thegeared architecture 48. Once communicated through the gearedarchitecture 48 the oil is radially expelled through the oil recoverygutter 76 in the ring gear 64 by various paths such as oil passage 78.

With reference to FIG. 3, an oil system 80 is schematically illustratedin block diagram form for the geared architecture 48 as well as othercomponents which receive oil. It should be appreciated that the oilsystem 80 is but a schematic illustration and is simplified incomparison to an actual oil system. The oil system 80 generally includesan oil tank 82, a supply pump 84, a sensor 86, an oil filter 88, astarter 90, a fuel pump 92, the geared architecture 48, the scavengepump 94, and a sensor 96. The oil flow to the geared architecture 48 maybe considered an oil supply path 100, and the oil flow from the gearedarchitecture 48 can be considered an oil return path 102. A multiple ofchip collectors 104 may be located in the supply path 100 and the returnpath 102 to capture ferrous debris.

The sensors 86, 96 may utilize two outer field coils to generate a drivesignal (high frequency cyclic signal), causing equal and opposingmagnetic fields (M-field). The ferrous particle strength of the M-fieldcreated by one field coil after another, causes the processed signal tobe a period of a sine wave. The nonferrous particle weakens the M-fieldcreated by one field coil after another, causing the similar sine wavebut in opposing polarity. Generally, the signal magnitude isproportional to the size of particle and the signal width is inverselyproportional to the particle speed.

With Reference to FIG. 4, a debris management system 110 generallyincludes a controller 120 in communication with the sensors 86, 96. Thesensors 86, 96 may be in-line oil debris monitor sensors. The debrismanagement system 110 protects against unexpected phase angle changeswhich may affect individual oil debris monitors caused by replacement orredesign of other components in the system, such as a signal wireharness, that can drastically influence the phase angle.

The controller 120 generally includes a control module 122 that executeslogic 124 (FIG. 5) to actively calculate and monitor the oil debrismonitor phase angle with regards to particle detection and systemdeterioration, stability and health. The functions of the logic 124 aredisclosed in terms of functional block diagrams, and it should beappreciated that these functions may be enacted in either dedicatedhardware circuitry or programmed software routines capable of executionin a microprocessor-based electronics control embodiment. In oneexample, the control module 122 may be a portion of a flight controlcomputer, a portion of a Full Authority Digital Engine Control (FADEC),a stand-alone unit, or other system.

The control module 122 typically includes a processor 122A, a memory122B, and an interface 122C. The processor 122A may be any type of knownmicroprocessor having desired performance characteristics. The memory122B may be any computer readable medium which stores data and controlalgorithms such as the logic 124 as described herein. The interface 122Cfacilitates communication with other components such as the sensors 86,96, as well as remote systems such as a ground station, Health and UsageMonitoring Systems (HUMS), or other system.

The oil debris monitor phase angle is used to classify detected particletypes (ferrous/nonferrous) through a mathematical transformation. Thephase angle is calibrated by pulling a particle of known type and sizethrough the sensor and using the ratio of I and Q channel amplitude andtrigonometric relationships to calculate an optimum (for classification)phase angle. The I channel is the In-phase, or real component and the Qchannel is the Quadrature (90° shift of real component). As will befurther described below, this principle is applied to background noisein the system by calculating the slope of the relationship between noisepeaks of the oil debris monitor I and Q data channels.

With reference to FIG. 5, the logic 124 for particle analysis with thecontroller, initially includes receipt of raw oil debris monitor datafrom either or both of the sensors 86, 96 into the controller for signalconversion from analog to digital (202). The raw data is stored in acontroller buffer (204). The buffer for the controller is continuallyfilled with raw data that flows as a constant stream such that a runningon-board calculation may be performed.

The phase angle of the signal (206; FIG. 6) is calculated from the noiseusing the raw oil debris monitor data in the controller buffer. Thephase angle may then be used for a system health assessment (208) andmay be transmitted (210) for further processing in the controller aswell as transmitted with system health data for off-board healthmonitoring (212). The system health assessment may include, for example,particle count, particle type classification, size and mass estimates,system availability, debris count rates, and other metrics. The A/Dconverted raw oil debris monitor signals are filtered and phase angleadjusted (214) within the controller, then the particle detectionalgorithm executes (216). Typically, the particle signal will distributeinto both I and Q channels due to phase angle misalignment between thedrive signal and mixer signal as caused by system impedance in thedriving and sensing circuitry. The phase angle adjustment (FIG. 7)realigns the particle signal distribution such that the ferrous particlesignal is maximized in the ferrous channel and the nonferrous particlesignal is maximized in then nonferrous channel. The particleclassification and size data from the particle detection algorithm isthen transmitted (218) for off-board health monitoring.

With reference to FIG. 9, a method 300 for actively calculating andmonitoring the oil debris monitor phase angle on-board the controllerinitially includes accessing the oil debris monitor raw data from thecontroller buffer which has been obtained from the sensors 86, 96 (204;FIG. 5). Next, a polar plot of the I and Q data is created from thebackground noise 400 only (step 304; FIG. 9). Essentially, the noise 400(FIG. 10) is isolated as compared to the particle signal 406 (FIG. 8)from actual particles.

Next, noise peaks (402; FIG. 9) which are the outer bounds of the polarplot are identified (step 306). Noise peaks are the outer bounds of thepolar plot that may not be attributed to a particle.

A linear noise peak regression (408; FIG. 9) of the I and Q data noisepeaks is then performed (step 308). The linear noise peak regressiongenerates a line with a slope that is used to calculate phase. Forexample, linear regression may be utilized generally or specificallywith the peaks. Next, a slope of linear noise peak regression iscalculated (step 310) then converted to phase angle (step 312). Theslope may be determined with the arc tan formula (FIG. 10). In currentsystems, the phase angle is a fixed value in the software based oncalibration tests and peaks of the particles are utilized to calculatethe phase angle. In contrast, by focusing on the noise, the phase angleis calculated in essentially real time. For example, the phase angle maybe a calculated value that is about 125% (FIG. 10) compared to asoftware fixed value (FIG. 11) based on the same raw ODM channel data(FIG. 12). The noise provides a calculated phase angle to show theferrous particle without any nonferrous excitation. For example, theplanner plot shows the fixed phase angle of the system (FIG. 10)compared to use of noise feedback (FIG. 11).

The calculated phase angle may then be stored (step 314) and/ortransmitted (step 316) for health and stability assessment. The systemis thus identified as healthy when the phase angle is stable (FIG. 13)compared to an unhealthy system that is not stable to provide anotherpoint for off-board trending.

With reference to FIG. 14, the logic 124 for particle analysis (FIG. 5)with the controller 120 may, in another embodiment, include particledetection logic 500 via fast Fourier transforms (FFT) of the I and Qdata stored in the controller buffer. The fast Fourier transform (FFT)is an algorithm that samples a signal over a period of time (or space)and divides it into its frequency components which are single sinusoidaloscillations at distinct frequencies each with their own amplitude andphase. The particle detection logic 500 provides an automated method tocorrectly assess particle characteristics that, even in a noisy system,can generate a particle count. The method will lead to rejection ofsignals that meet the requirements for a particle but do not have aparticle shape, thus reducing false detections.

Initially, the particle detection logic 500 includes execution of FFT onthe I and Q data (502). The resultant I and Q FFT data is then processedto extract an overall shape (504). The shape of the I and Q FFT data isthen analyzed (506) and compared to a predetermined shape thatrepresents the presence of a particle. The shape resulting from the Iand Q FFT data may not be a perfect sinusoid but a bow shape (FIGS.15-20). When comparing the FFT of the signal with no particle present(FIG. 15) to the FFT of the signal with a particle present (FIG. 16),the bow shape is identifiable. The FFT of the particle alone (FIG. 17)is responsible for the bow shape (FIG. 18). Removing the particlecontribution of the FFT (FIG. 17) from the signal with the particlepresent (FIG. 16), it is observed that the resultant FFT is similar to(FIG. 15; FFT where no particle is present). More significantly, thesmoothed and normalized FFT shape extracted (FIG. 16) can bemathematically compared to the particle FFT (FIG. 17) to identifysimilarity (FIG. 20). The I and Q FFT data in the buffer is analyzed forthe predetermined shape at a predetermined range of frequenciesrepresentative of the oil flow rate.

If the difference between the particle I and Q FFT data and the particleremoved I and Q FFT data is significant. The level of significance wouldvary based on applications. An example would be to use expected FFTshapes. At each frequency in the expected bow range (in this case 0 to400 Hz), there is a maximum difference of, for example, +/−0.1, and thefrequencies corresponding to the maximum of each bow is, for example,within 50 Hz], then it can be determined that a particle like signalexists. That is, if there is a shape similarity, the logic 124 continuesas described above with respect to FIG. 5. If there is no shapesimilarity, the logic 124 for particle analysis is bypassed as noparticle has been detected.

With reference to FIG. 21, the logic 124 for particle analysis (FIG. 5)with the controller 120 may, in another embodiment, include particlerejection logic 600 via fast Fourier transforms (FFT) of the ferrous ornonferrous particle data after the particle detection algorithm executes(216; FIG. 5). To confirm that a true particle has been detected, theshape of the ferrous and nonferrous FFT data, the frequency center, andthe lobe width requirements compared to that of a particle are checked.That is, the particle will typically produce a sinusoidal excitation onthe ferrous and nonferrous data channel, and given the flow rates of thesystem and the range of frequencies that the shape covers, the detectedparticle is either accepted or rejected. An example of a rejectedparticle would be an electrical anomaly that is not a particle andvisually is not particle like, but meets the symmetry, amplitude, andlobe width requirements in the software such as in the filter and phaseadjustment stage.

Initially, the particle rejection logic 600 includes execution of FFT onthe ferrous or nonferrous particle data (602). The resultant ferrous andnonferrous FFT data is then processed to extract the FFT shape (604).The shape of the ferrous or nonferrous particle FFT data is thenanalyzed (606) and compared to an expected shape. If there is a shapesimilarity, the logic 124 for particle analysis continues as describedabove with respect to FIG. 5. If there is no shape similarity, theparticle is rejected from analysis by the logic 124.

With reference to FIG. 22, the logic 124 for particle analysis (FIG. 5)with the controller 120 may, in another embodiment, include particlerejection logic 700 based on the understanding that a true particlesignal is sinusoidal in nature with symmetric lobes. A processed(filtered and phase adjusted) ferrous/non-ferrous signal is utilized forparticle detection. The particle will typically produce a sinusoidalexcitation on the ferrous and nonferrous data channel, and given theflow rates of the system and the range of frequencies that the shapecovers, the detected particle is then either accepted or rejected. Anexample of a rejected particle would be an electrical anomaly that isnot a particle and visually is not particle like, but meets thesymmetry, amplitude, and lobe width requirements in the software.

A processed (filtered and phase adjusted) ferrous/non-ferrous signal isexclusively utilized for particle detection and signal rejection.Initially, the particle rejection logic 700 uses the processed ferrousand nonferrous single coupled with output from the particle detectionalgorithm (216; FIG. 5) to disposition a candidate signal. The rejectionlogic may, for example, account for lobe and peak symmetry, and width,in the processed signal, but does not leverage critical information inthe raw signal that is lost in the filtered and transformed ferrous andnon-ferrous data. A true particle signal is sinusoidal in nature withsymmetric lobes in the raw I, Q signal, and that symmetry is preservedin the transformed ferrous and non-ferrous signal. The filter and phaseadjustment stage can convert a raw signal that does not meet symmetryrequirements into a signal accepted as particle.

Next, the candidate signals proceed to a symmetry check (704). That is,the raw I and Q channel data is processed to confirm symmetry after theferrous and nonferrous signal lobe peak symmetry (702) is confirmed. Thesymmetry check (704) compares the symmetry between the ferrous andnonferrous signals and the I and Q channel data to determine if thecandidate signal is a particle. Utilizing the distorted ferrous andnon-ferrous signal alone may lead to an invalid signal being accepted asa particle. The I and Q channel data itself, however, may not beparticle like, and a symmetry check on this data can be utilized forrejection. In one embodiment, symmetry check (704) is performed viadetermination of a symmetry factor:Symmetry factor=peak/absolute value (valley)  [1]

The example I and Q channel data (FIG. 23) is converted into ferrous andnonferrous signal data (FIG. 24). The ferrous and nonferrous signal datais processed and would incorrectly accept this signal as a particle. Theraw I and Q channel data, however, is not particle like, and thesymmetry check (704) on this data would result in rejection. Forexample, if the symmetry factor is greater than the threshold (e.g., 1-4FIG. 25), the particle is rejected from analysis by the logic 124.

Input data (FIG. 26) is converted into the ferrous and nonferrous signaldata (FIG. 27). The ferrous and nonferrous signal data is processed andwould accept this signal as a particle. The raw I and Q data, however,is not relatively symmetric like a particle, so a symmetry check (704)on this data would result in rejection. For example, if the symmetryfactor is greater than the threshold (e.g., 1-4 FIG. 28), the particleis rejected from analysis by the logic 124.

With reference to FIG. 29, the example I and Q channel data lobe peaksymmetry (702) is confirmed and the lobes have similar symmetry as theprocessed ferrous and nonferrous signals used for detection (FIG. 30).That is, the symmetry check (704) on this data in accordance with themethod 700 would result in acceptance. That is, the symmetry factor isbelow a predetermined threshold (e.g., 1-4; FIG. 31), the logic 124 forparticle analysis continues as described above with respect to FIG. 5.

The logic 700 leverages the observation that, for a true particledetection, the raw signal and processed signal will have a similar,symmetric, sinusoidal shapes. When a candidate particle is identified,the raw signal is then checked for symmetry against the requirements andagainst the detected particle. The logic 700 will identify the caseswhere a non-symmetric, non-particle like signal is distorted into asymmetric shape that will be accepted by the state machine logic. Thelogic 700 provides an additional validity check for candidate particlesand a measure of sensing system health. Adding this functionality onon-board software would both reduce the cost and burden associated withnuisance detection and aid with fault isolation. The current technologyuses a state machine to process a filtered and phase adjusted ferrousand nonferrous signal derived from the raw I and Q channel data. The rawdata is not used in current technology. The current technology canaccepts noise due to a non-particle like signal that, with parallelprocessing of the raw I and Q data, could be rejected.

The method 300 dynamically identifies the effect of phase angle changeand adopts the appropriate phase angle. The real time phase angle can bedetermined on-board and used to provide a more accurate particle sizeand classification to determine the health of the diagnostic system andalso provide a prognostic tool for predicting the state of the system inthe future. The particle detection logic 500 and the particle rejectionlogic 600 and/or 700 provide an automated, real time check of acandidate particle viability. This removes human analysis from datareview and provides for on-board discretion, reducing time and expenseof data review.

Although particular step sequences are shown, described, and claimed, itshould be appreciated that steps may be performed in any order,separated or combined unless otherwise indicated and will still benefitfrom the present disclosure.

The foregoing description is exemplary rather than defined by thelimitations within. Various non-limiting embodiments are disclosedherein; however, one of ordinary skill in the art would recognize thatvarious modifications and variations in light of the above teachingswill fall within the scope of the appended claims. It is therefore to beappreciated that within the scope of the appended claims, the disclosuremay be practiced other than as specifically described. For that reason,the appended claims should be studied to determine true scope andcontent.

What is claimed:
 1. A method for determining the presence of a particlewhile actively calculating and monitoring oil debris monitor phase anglein an oil system, comprising: a) collecting I and Q channel data from anoil debris monitor sensor; b) determining whether the I and Q channeldata is symmetric; c) processing the I and Q channel data to identify aferrous and nonferrous signal in response to the I and Q channel databeing symmetric in step b); d) processing the ferrous and nonferroussignals to determine if the particle is present; e) determining asymmetry factor from the I and Q channel data in response to theparticle present in step d); and f) confirming that the particle ispresent from the symmetry factor.
 2. The method as recited in claim 1,wherein step b) comprises determining if lobe peaks are symmetric. 3.The method as recited in claim 1, wherein the ferrous and nonferroussignals are used for particle detection.
 4. The method as recited inclaim 1, wherein said step d) comprises filtering and phase adjustingthe ferrous and nonferrous signals.
 5. The method as recited in claim 1,further comprising continually filling a buffer of a controller with theI and Q channel data.
 6. The method as recited in claim 1, furthercomprising converting the I and Q channel data to digital I and Q datawithin a controller on-board an aircraft.
 7. The method as recited inclaim 6, further comprising locating the oil debris monitor sensorwithin an oil supply path.
 8. The method as recited in claim 6, furthercomprising locating the oil debris monitor sensor within an oil returnpath.
 9. The method as recited in claim 1, wherein the symmetryfactor=peak/absolute value of the I and Q channel data.
 10. The methodas recited in claim 9, wherein the particle is rejected in response tothe symmetry factor being less than a threshold.
 11. The method asrecited in claim 10, wherein the threshold is between 1-4.
 12. Themethod as recited in claim 9, wherein the symmetry factor is applied tothe I channel data.
 13. The method as recited in claim 9, wherein thesymmetry factor is applied to the Q channel data.
 14. An oil system fora gas turbine engine, comprising: an oil flow path; an in-line oildebris monitor sensor; and a control system in communication with thein-line oil debris monitor sensor to collect I and Q channel data fromthe oil debris monitor sensor; determine whether the I and Q channeldata is symmetric; process the I and Q channel data to identify aferrous and nonferrous signal in response to the I and Q channel databeing symmetric; process the ferrous and nonferrous signals to determineif the particle is present; determine a symmetry factor from the I and Qchannel data in response to the particle present; and confirm that theparticle is present from the symmetry factor.
 15. The system as recitedin claim 14, wherein the oil flow path is in communication with a gearedarchitecture of the gas turbine engine.
 16. The system as recited inclaim 14, wherein the oil flow path is an oil supply path.
 17. Thesystem as recited in claim 14, wherein the oil flow path is an oilreturn path.
 18. The system as recited in claim 14, further comprising achip collector within the oil flow path.
 19. The system as recited inclaim 14, wherein the control system comprises a controller.